Electricity stealing prevention method

Abstract

The invention relates to the technical field of power ammeters, in particular to an electricity stealing prevention method which comprises the following steps: S1, installing an intelligent ammeter; s2, data acquisition; s3, data analysis; and S4, carrying out anomaly detection and alarming. Through the intelligent monitoring system, abnormal electricity consumption behaviors can be rapidly identified, an alarm is given in time, and electricity stealing behaviors are effectively reduced. The economic loss caused by electric power theft is reduced, and the income and the operation efficiency of an electric power company are improved; manual intervention is reduced; an automatic detection and alarm system reduces the dependence on manual inspection, and the working efficiency is improved.

Description

Technical Field

[0001] The invention relates to the technical field of electric power meters and is an anti-electricity theft method. Background Art

[0002] Traditional power management systems usually rely on manual inspections and traditional meters to detect power usage. This approach has the following main problems: 1. Insufficient real-time monitoring capabilities: Traditional meters can generally only provide periodic readings and lack the ability to monitor power usage in real time. This makes it difficult for power companies to detect and respond to power theft in a timely manner, leading to increased economic losses. 2. Limited detection accuracy: Traditional power management systems mainly rely on comparing meter readings with expected power usage patterns to detect power theft, but this method is slow to respond to complex power theft methods and hidden power theft patterns, and has insufficient detection accuracy. 3. Dependence on manual inspections: Traditional systems rely on manual inspections to detect potential power theft problems, and the inspection frequency and scope are limited, making it difficult for the system to fully monitor power theft in a large-scale power network. 4. Data processing lag: Traditional power management systems often require manual analysis after data collection, and the speed of data processing and anomaly detection is slow, which makes it difficult to meet the requirements of modern power systems for rapid response and real-time processing. 5. Complex system maintenance: The maintenance and upgrade of traditional systems usually require a lot of manual intervention and technical support, and the system maintenance cost is high, affecting the long-term operation and reliability of the system.

[0003] In order to solve the above problems, smart meters and data analysis technologies have been gradually introduced in recent years to improve the real-time and accuracy of power theft detection. Smart meters have real-time data collection and remote communication functions, which can provide detailed data on power usage, while data analysis systems can more accurately identify abnormal power usage behaviors using advanced algorithms and models. However, existing intelligent anti-power theft technologies still have problems such as complex system integration, high cost, and insufficient data analysis accuracy. Summary of the invention

[0004] The present invention provides an anti-electricity theft method, which overcomes the deficiencies of the above-mentioned prior art and can effectively solve the problems of the existing intelligent anti-electricity theft technology, such as complex system integration, high cost, and insufficient data analysis accuracy.

[0005] The technical solution of the present invention is achieved by the following measures: an anti-electricity theft method comprises the following steps: S1. Install smart meters; S2. Data collection; S3. Data analysis; S4. Abnormal detection and alarm.

[0006] As a preferred solution: S2: Data collection: Steps: acquiring power consumption data from smart meters in real time or periodically; recording current, voltage, and power parameters; and transmitting the data to a central database for processing.

[0007] As a preferred solution: S3: Data analysis: Step: Detect electricity usage patterns using data analysis algorithms; identify unusual electricity usage behaviors such as abnormal consumption and sudden electricity usage; compare historical data with normal patterns to detect potential electricity theft behaviors.

[0008] As a preferred solution: S4: Abnormal detection and alarm: Step: setting a threshold value and detecting abnormal situations according to the analysis results; triggering an alarm system, and providing a detailed abnormal report and analysis results.

[0009] As a preferred solution: the alarm system is SMS, email or system notification.

[0010] (III) Beneficial effects Compared with the prior art, the present invention provides an anti-electricity theft method, which has the following beneficial effects: 1. Improve power management efficiency: Real-time data collection and analysis can help power companies manage power resources more effectively and optimize power distribution.

[0011] 2. Timely detection and response: The intelligent monitoring system can quickly identify abnormal electricity usage behavior, issue alarms in a timely manner, and effectively reduce the occurrence of electricity theft.

[0012] 3. Reduce economic losses: Reduce economic losses caused by power theft and increase power company revenue and operational efficiency.

[0013] 4. Reduce manual intervention: Automated detection and alarm systems reduce reliance on manual inspections and improve work efficiency. DETAILED DESCRIPTION

[0014] The following will be combined with the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0015] Embodiment 1: In actual use, the anti-electricity theft method includes the following steps: S1. Demand analysis and system design; S2. Installation of smart meters; S3. Data collection; S4. Data analysis; S5. Abnormal detection and alarm; S6. On-site verification; S7. Taking measures; S8. System optimization, the S1: Demand analysis and system design: purpose: determine the system requirements and functions; steps: understand the needs and challenges of the power supply company; design the system architecture, including hardware and software components; determine the methods of data collection, processing and analysis, the S2: Installation of smart meters: purpose: monitor power consumption; steps: install smart meters that support remote communication; configure meter parameters, including data transmission frequency and data format; ensure that the communication between the meter and the central monitoring system is normal, the S3: Data collection: purpose: collect electricity consumption data for analysis; steps: obtain electricity consumption data from smart meters in real time or regularly; record parameters such as current, voltage, power, etc.; transmit data to the central database for processing, the S4: Data analysis: purpose: Identify abnormal electricity usage; Steps: Use data analysis algorithms to detect electricity usage patterns; Identify unusual electricity usage behaviors such as abnormal consumption and sudden electricity usage; Compare historical data with normal patterns to detect potential electricity theft, S5: Abnormal detection and alarm; Purpose: Respond to possible electricity theft events in a timely manner; Steps: Set thresholds and detect abnormal situations based on analysis results; Trigger alarm systems (including SMS, emails, or system notifications); Provide detailed abnormality reports and analysis results, S6: On-site verification: Purpose: Verify whether there is electricity theft; Steps: Arrange technicians or law enforcement personnel to conduct on-site inspections; Check the installation status of the meter, cable connections, etc.; Use detection tools to confirm whether there is illegal wiring or other means of electricity theft, S7: Take measures: Purpose: Deal with confirmed electricity theft; Steps: Punish or prosecute confirmed electricity theft; Modify or repair meters and power systems to prevent further electricity theft; Take necessary legal actions or punish those responsible for electricity theft, S8: System optimization: Purpose: Improve the accuracy and reliability of the system; steps: collect and analyze feedback to evaluate system performance; update and optimize data analysis models and alarm systems; regularly maintain and upgrade smart meters and related equipment.

[0016] Embodiment 2 1. System Architecture System Objective: Determine system requirements and design an appropriate architecture to effectively detect and prevent power theft. Steps: 1. Requirements Analysis: Understand the challenges faced by power supply companies, including power losses, frequency and types of power theft. Determine the functional requirements of the system, including real-time data monitoring, anomaly detection and alarm functions.

[0017] 2. System architecture design: Hardware components: Smart meters: Equipped with sensors and communication modules to monitor electricity consumption in real time.

[0018] Data acquisition device: used to receive smart meter data and transmit it to the central database.

[0019] Central Server: Stores and processes data transmitted from individual smart meters.

[0020] Alarm system: includes SMS, email or system notification functions for alarm after abnormal detection.

[0021] Software components: Data processing module: used to receive, store and process power consumption data.

[0022] Data Analysis Module: Uses analytical algorithms to process data and identify abnormal patterns.

[0023] User Interface: The interface provided to power company operators to view and manage data.

[0024] System optimization module: Regularly update and optimize data analysis algorithms and system configurations.

[0025] 3. Data collection, processing and analysis methods: Data collection: Obtain real-time electricity consumption data including current, voltage and power through smart meters.

[0026] Data processing: The collected data is transferred to the central database for storage and preliminary processing.

[0027] Data analysis: Use the data analysis module to conduct in-depth analysis of data and identify potential electricity theft.

[0028] 2. Data Analysis Purpose: To identify abnormal electricity usage behavior and detect possible electricity theft.

[0029] step: 1. Data Analysis Algorithm: Data Collection: Collect electricity usage data from smart meters, including timestamp, current (I), voltage (V), and power (P).

[0030] Anomaly Detection: Data preprocessing: remove noise and normalize the raw data.

[0031] Pattern Recognition: Mean analysis based on historical data: \[ \text{mean} = \frac{1}{N} \sum_{i=1}^{N} P_i \] Standard Deviation Analysis: \[ \text{Standard deviation} = \sqrt{\frac{1}{N1} \sum_{i=1}^{N} (P_i \text{mean})^2} \] Anomaly detection formula: \[ \text{Anomaly threshold} = \text{mean} + k \times \text{standard deviation} \] Among them, \( k \) is the set threshold coefficient, which is generally between 2 and 3.

[0032] Detection logic: When real-time data exceeds the abnormal threshold range, it is marked as abnormal data.

[0033] 2. Abnormal behavior identification: Power usage pattern analysis: Compare normal power usage patterns to identify sudden or non-pattern power usage behaviors.

[0034] Data comparison: Compare current data with historical data to determine whether there are any anomalies.

[0035] 3. Abnormality detection and alarm (based on claim 6) Purpose: To respond promptly to possible electricity theft incidents.

[0036] step: 1. Anomaly Detection: Set threshold: Set the anomaly detection threshold based on the data analysis results.

[0037] Real-time monitoring: The monitoring system detects in real time whether the power consumption data exceeds the set abnormal threshold.

[0038] 2. Alarm system: Alarm trigger: When an abnormal situation is detected, the alarm system is triggered.

[0039] Notification method: Send SMS, email or system notification to power company staff.

[0040] Detailed Report: Generate an abnormal report, including abnormal time, abnormal data value, detection reason and possible electricity theft behavior analysis.

[0041] 3. On-site verification: Inspection arrangement: notify technicians or law enforcement personnel to go to the site for inspection; Inspection contents: Confirm the installation status of the meter and check the cable connection; Use special detection tools to check for illegal wiring or other means of stealing electricity.

[0042] This embodiment describes in detail the system architecture, data analysis method, and abnormal detection and alarm process of the intelligent anti-electricity theft method. Through these specific steps and formulas, the detection and prevention of electricity theft in the power system can be better achieved.

[0043] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for preventing electricity theft, characterized in that: The following steps are involved: S1. Install smart meters; S2. Data collection; S3. Data analysis; S4. Anomaly detection and alarm.

2. The anti-electricity theft method according to claim 1, characterized in that: S2: Data collection: Steps: acquiring power consumption data from smart meters in real time or periodically; recording current, voltage, and power parameters; and transmitting the data to a central database for processing.

3. The anti-electricity theft method according to claim 1 or 2, characterized in that: S3: Data analysis: Steps: Detect electricity usage patterns using data analysis algorithms; identify unusual electricity usage behaviors such as abnormal consumption and sudden electricity usage; compare historical data with normal patterns to detect potential electricity theft.

4. The anti-electricity theft method according to claim 1 or 2, characterized in that: S4: Abnormal detection and alarm: Steps: setting thresholds and detecting abnormal situations according to analysis results; triggering an alarm system, and providing detailed abnormality reports and analysis results.

5. The anti-electricity theft method according to claim 3, characterized in that: S4: Abnormal detection and alarm: Steps: setting thresholds and detecting abnormal situations according to analysis results; triggering an alarm system, and providing detailed abnormality reports and analysis results.

6. The anti-electricity theft method according to claim 4, characterized in that: The alarm system is SMS, email or system notification.

7. The anti-electricity theft method according to claim 5, characterized in that: The alarm system is SMS, email or system notification.